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Nogales E, Mahamid J. Bridging structural and cell biology with cryo-electron microscopy. Nature 2024; 628:47-56. [PMID: 38570716 PMCID: PMC11211576 DOI: 10.1038/s41586-024-07198-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 02/13/2024] [Indexed: 04/05/2024]
Abstract
Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.
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Affiliation(s)
- Eva Nogales
- Molecular and Cell Biology Department, Institute for Quantitative Biomedicine, University of California, Berkeley, CA, USA.
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Howard Hughes Medical Institute, Berkeley, CA, USA.
| | - Julia Mahamid
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
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Jiménez-Ortigosa C, Jiang J, Chen M, Kuang X, Healey KR, Castellano P, Boparai N, Ludtke SJ, Perlin DS, Dai W. Cryo-Electron Tomography of Candida glabrata Plasma Membrane Proteins. J Fungi (Basel) 2021; 7:120. [PMID: 33562124 PMCID: PMC7914498 DOI: 10.3390/jof7020120] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/18/2022] Open
Abstract
Fungal plasma membrane proteins have long been recognized as targets for the development of antifungal agents. Despite recent progress in experimental approaches and computational structural predictions, our knowledge of the structural dynamics and spatial distribution of these membrane proteins in the context of their native lipid environment remains limited. By applying cryo-electron tomography (cryoET) and subtomogram analysis, we aim to characterize the structural characteristics and spatial distribution of membrane proteins present in Candida glabrata plasma membranes. This study has resulted in the identification of the membrane-embedded structure of the fungal H+-ATPase, Pma1. Tomograms of the plasma membrane revealed that Pma1 complexes are heterogeneously distributed as hexamers that cluster into distinct membrane microdomains. This study characterizes fungal membrane proteins in the native cellular landscape and highlights the unique potential of cryoET to advance our understanding of cellular biology and biological systems.
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Affiliation(s)
- Cristina Jiménez-Ortigosa
- Hackensack Meridian Health-Center for Discovery and Innovation, 111 Ideation Way, Nutley, NJ 07110, USA;
| | - Jennifer Jiang
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA; (J.J.); (X.K.); (P.C.); (N.B.)
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - Muyuan Chen
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA; (M.C.); (S.J.L.)
| | - Xuyuan Kuang
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA; (J.J.); (X.K.); (P.C.); (N.B.)
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
- Department of Hyperbaric Oxygen, Central South University, Changsha 410008, China
| | - Kelley R. Healey
- Department of Biology, William Paterson University, 300 Pompton Road, Wayne, NJ 07470, USA;
| | - Paul Castellano
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA; (J.J.); (X.K.); (P.C.); (N.B.)
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - Nikpreet Boparai
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA; (J.J.); (X.K.); (P.C.); (N.B.)
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - Steven J. Ludtke
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA; (M.C.); (S.J.L.)
| | - David S. Perlin
- Hackensack Meridian Health-Center for Discovery and Innovation, 111 Ideation Way, Nutley, NJ 07110, USA;
| | - Wei Dai
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ 08854, USA; (J.J.); (X.K.); (P.C.); (N.B.)
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
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Ng CT, Gan L. Investigating eukaryotic cells with cryo-ET. Mol Biol Cell 2020; 31:87-100. [PMID: 31935172 PMCID: PMC6960407 DOI: 10.1091/mbc.e18-05-0329] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 11/25/2019] [Accepted: 11/29/2019] [Indexed: 01/06/2023] Open
Abstract
The interior of eukaryotic cells is mysterious. How do the large communities of macromolecular machines interact with each other? How do the structures and positions of these nanoscopic entities respond to new stimuli? Questions like these can now be answered with the help of a method called electron cryotomography (cryo-ET). Cryo-ET will ultimately reveal the inner workings of a cell at the protein, secondary structure, and perhaps even side-chain levels. Combined with genetic or pharmacological perturbation, cryo-ET will allow us to answer previously unimaginable questions, such as how structure, biochemistry, and forces are related in situ. Because it bridges structural biology and cell biology, cryo-ET is indispensable for structural cell biology-the study of the 3-D macromolecular structure of cells. Here we discuss some of the key ideas, strategies, auxiliary techniques, and innovations that an aspiring structural cell biologist will consider when planning to ask bold questions.
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Affiliation(s)
- Cai Tong Ng
- Department of Biological Sciences and Centre for BioImaging Sciences, National University of Singapore, Singapore 117543
| | - Lu Gan
- Department of Biological Sciences and Centre for BioImaging Sciences, National University of Singapore, Singapore 117543
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Gan L, Ng CT, Chen C, Cai S. A collection of yeast cellular electron cryotomography data. Gigascience 2019; 8:giz077. [PMID: 31247098 PMCID: PMC6596884 DOI: 10.1093/gigascience/giz077] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 05/09/2019] [Accepted: 06/10/2019] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Cells are powered by a large set of macromolecular complexes, which work together in a crowded environment. The in situ mechanisms of these complexes are unclear because their 3D distribution, organization, and interactions are largely unknown. Electron cryotomography (cryo-ET) can address these knowledge gaps because it produces cryotomograms-3D images that reveal biological structure at ∼4-nm resolution. Cryo-ET uses no fixation, dehydration, staining, or plastic embedment, so cellular features are visualized in a life-like, frozen-hydrated state. To study chromatin and mitotic machinery in situ, we subjected yeast cells to genetic and chemical perturbations, cryosectioned them, and then imaged the cells by cryo-ET. FINDINGS Here we share >1,000 cryo-ET raw datasets of cryosectioned budding yeast Saccharomyces cerevisiaecollected as part of previously published studies. These data will be valuable to cell biologists who are interested in the nanoscale organization of yeasts and of eukaryotic cells in general. All the unpublished tilt series and a subset of corresponding cryotomograms have been deposited in the EMPIAR resource for the community to use freely. To improve tilt series discoverability, we have uploaded metadata and preliminary notes to publicly accessible Google Sheets, EMPIAR, and GigaDB. CONCLUSIONS Cellular cryo-ET data can be mined to obtain new cell-biological, structural, and 3D statistical insights in situ. These data contain structures not visible in traditional electron-microscopy data. Template matching and subtomogram averaging of known macromolecular complexes can reveal their 3D distributions and low-resolution structures. Furthermore, these data can serve as testbeds for high-throughput image-analysis pipelines, as training sets for feature-recognition software, for feasibility analysis when planning new structural-cell-biology projects, and as practice data for students.
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Affiliation(s)
- Lu Gan
- Department of Biological Sciences and Centre for BioImaging Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543
| | - Cai Tong Ng
- Department of Biological Sciences and Centre for BioImaging Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543
| | - Chen Chen
- Department of Biological Sciences and Centre for BioImaging Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543
| | - Shujun Cai
- Department of Biological Sciences and Centre for BioImaging Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543
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